Amar S Bhogal1, Michele De Rui2, Donatella Pavanello2, Ilias El-Azizi1, Sadia Rowshan1, Piero Amodio2, Sara Montagnese3, Ali R Mani4. 1. Division of Medicine, University College London, London, UK. 2. Department of Medicine, University of Padova, Padova, Italy. 3. Department of Medicine, University of Padova, Padova, Italy. Electronic address: sara.montagnese@unipd.it. 4. Division of Medicine, University College London, London, UK. Electronic address: a.r.mani@ucl.ac.uk.
Abstract
BACKGROUND: Liver cirrhosis is associated with reduced heart rate variability (HRV), which indicates impaired integrity of cardiovascular control in this patient population. There are several different indices for HRV quantification. The present study was designed to: 1) determine which of the HRV indices is best at predicting mortality in patients with cirrhosis; 2) verify if such ability to predict mortality is independent of the severity of hepatic failure. METHODS: Ten minutes electrocardiogram was recorded in 74 patients with cirrhosis. Heart rate fluctuations were quantified using statistical, geometrical and non-linear analysis. The patients were followed-up for 18months and information was collected on the occurrence of death/liver transplantation. RESULTS: During the follow-up period, 24 patients (32%) died or were transplanted for hepatic decompensation. Cox's regression analysis showed that SDNN (total HRV), cSDNN (corrected SDNN), SD1 (short-term HRV), SD2 (long-terms HRV) and spectral indices could predict survival in these patients. However, only SD2 and cSDNN were shown to be independent of MELD in predicting survival. The prognostic value of HRV indices was independent of age, gender, use of beta blockers, and the aetiology of liver disease. CONCLUSION: Two HRV indices were identified that could predict mortality in patients with cirrhosis, independently of MELD. These indices are potentially useful tools for survival prediction.
BACKGROUND:Liver cirrhosis is associated with reduced heart rate variability (HRV), which indicates impaired integrity of cardiovascular control in this patient population. There are several different indices for HRV quantification. The present study was designed to: 1) determine which of the HRV indices is best at predicting mortality in patients with cirrhosis; 2) verify if such ability to predict mortality is independent of the severity of hepatic failure. METHODS: Ten minutes electrocardiogram was recorded in 74 patients with cirrhosis. Heart rate fluctuations were quantified using statistical, geometrical and non-linear analysis. The patients were followed-up for 18months and information was collected on the occurrence of death/liver transplantation. RESULTS: During the follow-up period, 24 patients (32%) died or were transplanted for hepatic decompensation. Cox's regression analysis showed that SDNN (total HRV), cSDNN (corrected SDNN), SD1 (short-term HRV), SD2 (long-terms HRV) and spectral indices could predict survival in these patients. However, only SD2 and cSDNN were shown to be independent of MELD in predicting survival. The prognostic value of HRV indices was independent of age, gender, use of beta blockers, and the aetiology of liver disease. CONCLUSION: Two HRV indices were identified that could predict mortality in patients with cirrhosis, independently of MELD. These indices are potentially useful tools for survival prediction.
Authors: Reem Satti; Noor-Ul-Hoda Abid; Matteo Bottaro; Michele De Rui; Maria Garrido; Mohammad R Raoufy; Sara Montagnese; Ali R Mani Journal: Front Physiol Date: 2019-02-19 Impact factor: 4.566
Authors: Tope Oyelade; Gabriele Canciani; Matteo Bottaro; Marta Zaccaria; Chiara Formentin; Kevin Moore; Sara Montagnese; Ali R Mani Journal: Front Physiol Date: 2020-12-09 Impact factor: 4.566
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